A MOLECULAR AND COMPUTATIONAL APPROACH TO ANALYZE THE BIOGENESIS OF THE POTASSIUM-CHLORIDE COTRANSPORTER 2 (KCC2), A NEURON-SPECIFIC PROTEIN IMPLICATED IN DISEASE

The concentration of intracellular and extracellular potassium is tightly regulated due to the action of various ion transporters which play vital roles in all organs and cell types. Unsurprisingly, defects in the biogenesis, function, and/or regulation of these proteins are linked to a range of catastrophic human diseases. The neuron-specific potassium chloride co-transporter 2 (KCC2) is critical for brain development and regulates γ-aminobutyric acid-dependent inhibitory neurotransmission. KCC2 dysregulation is implicated in neurodevelopmental disorders, including schizophrenia, autism, and epilepsy. Based on its complex architecture and function, reduced cell surface expression and/or activity have been reported when some disease-associated mutations are present in the gene encoding the protein, SLC12A5. These data suggest that KCC2 might be inherently unstable, thus making it susceptible to cellular quality control pathways that degrade misfolded proteins. For my dissertation research, I sought to explore the protein quality control mechanisms that regulate KCC2 and characterize select mutants that have been implicated in disease. In this thesis, I begin by reviewing the disease relevance, structure, and protein quality control pathways that regulate potassium transporters in the cell. From here, I report my endeavors to examine KCC2 stability and/or maturation in five model systems: yeast, HEK293 cells, primary rat neurons, and rat and human brain synaptosomes. This work details the first comparison into the influence that the cellular and membrane environments have on several fundamental KCC2 properties. I also acknowledge the advantages and disadvantages of each system to set the stage for the investigation of select KCC2 disease-associated mutations expressed in HEK293 cells. In this next area of study, I identify which KCC2 mutants are maturation-defective and are depleted from the cell surface. To determine whether KCC2 maturation could be predicted, I then employed three computational pathogenicity predictors. Indeed, a pathogenicity score using one program, Rhapsody, correlates with defects in KCC2 ER-to-Golgi transport, and this algorithm outperformed two other pathogenicity predictors. These data demonstrate that a bioinformatic tool can predict the efficiency of ER exit and can be used to develop hypotheses on defects associated with other disease-associated SLC12A5 alleles as they are identified.